Thus, a question we ask is how can we restrict such illicit activities in cryptocurrency-based blockchain? There are many machine learning (ML) based techniques that have been proposed to detect suspicious accounts are not only based on the transaction history (behavior based) [1]}, [2]}, [3]}, [4]} but also utilise the meta-data information attached to the address [5]}. Further, services such as Chainalysishttps://www.chainalysis.com/ perform a dynamic exploration of the blockchain through use of proprietary ML algorithms. Such services and ML-based approaches are not integrated with the blockchain infrastructure. They operate outside the blockchain and have characteristics such as using the transaction history, being paid, dependent on ground-truth information, and are computationally expensive. Moreover, few approaches define reputation of user in the blockchain network using various mechanisms that although are behavior oriented but are either communication expensive [6]}, maintain a side chain [7]}, or biased [8]}.
